1. Field of the Invention
The present invention relates to a system for designing a configuration in accordance with human impressions associated with the configuration to be designed.
2. Description of the Background Art
A system for designing an interior configuration of a house called HULIS (Human Living System) has been proposed for example in the Electronic Information Society Publication, supplement, Vol. 3, pp. 245-247, March 1988, which is schematically shown in FIG. 1.
This system comprises a computer unit 101 having a processing unit 107, a knowledge data-base 110, and a graphic data-base 120; an input unit 103; and a display unit 105.
The knowledge data-base 110 includes an adjective data-base 111 which memorizes knowledges on a number of evaluation terms in forms of adjectives expressing human impressions associated with each design element such as gorgeous, spacious, relaxed, etc. and various relationships among the evaluation terms; and an image data-base 112 which memorizes knowledges on a number of design elements representing various forms of each component of a house such as an entrance, a bath room, a living room, a kitchen, bed room, etc. and various relationships between the evaluation terms and the design elements.
Thus, when an operator enters a particular component such as "bed room" and a desired evaluation term such as "spacious" through the input unit 103, the processing unit 107 searches through the knowledge data-base 110 to infer and extract the most appropriate design element for that component of "bed room" with that evaluation term "spacious" among those memorized in the knowledge data-base 110. Then, the processing unit 107 processes the extracted design element graphically by using a shape data-base 121 and a color data-base 122 of the graphic data-base 120, such that the extracted design element can be displayed in an appropriately processed form on the display unit 105.
Such a system for designing an interior configuration of a house can also be utilized as a system for designing an interior configuration of an automobile by constructing the knowledge data-base 110 in terms of design elements and evaluation terms suitable for an automobile interior, as disclosed in U.S. patent application Ser. No. 07/627,283 (1990).
In this case, the knowledge data-base 110 includes an adjective data-base 111 which memorizes knowledges on a number of evaluation terms in forms of adjectives expressing human impressions associated with each design element for an automobile interior such as gorgeous, spacious, suitable for fast driving, etc. and various relationships among the evaluation terms and an image data-base 112 which memorizes knowledges on a number of design elements representing various forms of each component of an automobile interior such as an instrument panel, a meter cluster, a center cluster, etc. and various relationships between the evaluation terms and the design elements.
Here, the knowledge data-base 110 is prepared by carrying out an evaluation term compiling operation to collect the appropriate evaluation terms, and a sense evaluation experiment in which samples of impressions associated with each design element are collected from a number of test persons in order to establish the relationships between the evaluation terms and the design elements empirically.
For example, as shown in FIG. 2, the relationships among the evaluation terms in the adjective data-base 111 can be given in terms of data on factor loads for the evaluation terms obtained by the factor analysis of the compiled evaluation terms. Here, the factors are derived by using the multivariate analysis and each factor load expresses a degree to which each evaluation term is related to each factor. In this case of FIG. 2, those evaluation terms for which the factor loads for some factor are similarly large can be considered as closely related in that respect. This adjective data-base 111 is utilized in finding a term similar to an input evaluation term which has not been utilized in the sense evaluation experiment to prepare the image data-base 112.
Now, as shown in FIG. 3, the design elements includes a number of items such as a meter size and an instrument panel thickness, and each item is divided into a plurality of categories representing a plurality of possible choices for each item such as large, medium, and small for the meter size.
Then, the actual impressions experienced by a plurality of test persons upon seeing a design element corresponding to each category of each item are compiled and analyzed by the multivariate analysis, such that as shown in FIG. 4 the relationships between the evaluation terms and the design elements in the image data-base 112 can be given in terms of partial regression coefficients (correlation coefficients). In this case of FIG. 4, those categories (marked by asterisks in FIG. 4) for which the absolute value of the partial regression coefficient for each evaluation term is largest among the categories for the respective item can be considered as most influential to that evaluation term, and the signs of the partial regression coefficients indicate the positive or negative influence.
On the other hand, the graphic data-base 120 includes a shape data-base 121 which memorizes data on shapes for various design elements; and a color data-base 122 which memorizes data on colors for various design elements.
As shown in FIG. 5, the shape data-base 121 memorizes graphic data on a basic framework BF and various units for filling in the basic framework BF such as an instrument panel unit IP, a meter cluster unit MC, and a center cluster unit CC, so as to obtain a complete configuration CL. Each unit is constructed from a plurality of items of the design elements, so that there are as many patterns for each unit as a product of a number of categories for each item included. For example, a steering wheel is constructed from three items including a number of spokes, a pad size, and a steering wheel radius, where a number of spokes has three categories (two, three, four), and a pad size has three categories (large, medium, small), while the steering wheel radius has three categories (large, medium, small), then there are 3.times.3.times.3=27 patterns prepared for the steering wheel.
The color data-base 122 memorizes data on colors by which each design element is to be colored. For example, in the steering wheel, the pad can be colored in grey, the spokes can be colored in silver, and the remaining part can be colored in dark gray.
Referring now to FIG. 6, the designing operation of this designing system will be described.
First, at the step S11, an operator enters an input evaluation term such as "easy to concentrate" for instance, through the input unit 103.
Then, at the step S12, an appropriate adjective processing is applied to the input evaluation term, such that when the input evaluation term is not present in the image data-base 112 prepared by the sense evaluation experiment, the term similar to this input evaluation term is searched out by using the adjective data-base 111.
Next, at the step S13, an inference processing is carried out by the processing unit 107 such that those categories in the knowledge data-base 110 for which the partial regression coefficient for this evaluation term of "easy to concentrate" is maximum among the categories of the respective item are inferred and extracted by the processing unit 107.
Here, in a case the operator enters two input evaluation terms such as "easy to concentrate" and "spacious" for instance, the partial regression coefficients for these two evaluation terms are summed for each category of each item, and those categories in the knowledge data-base 110 for which the sum of the partial regression coefficients for these two evaluation terms is maximum among the categories of the respective item are inferred and extracted by the processing unit 107.
Then, at the step S14, the following graphic processing is carried out by the processing unit 107 and the graphic data-base 120. First, the pattern corresponding to the extracted categories of the design elements is obtained by the processing unit 107 by using the shape data-base 121, so as to obtain the appropriate units to fill in the basic framework BF are constructed. Then, the obtained units are combined on the basic framework BF according to the flow chart shown in FIG. 7 to obtain the complete configuration CL. Namely, the basic framework BF is called up at the step S21, on which the instrument panel is superposed at the step S22, the meter cluster on which the steering wheel is added at the step S23 and the meters are added at the step S24 is superposed at the step S25, a center cluster on which a gear shift level is added at the step S26 is superposed at the step S27, a door is superposed at the step S28, and a seat is superposed at the step S29. Then, each design element in the complete configuration CL is colored according to the color data-base 122. Finally, the colored complete configuration is displayed on the display unit 105. For example, for the input evaluation term of "chic" a display shown in FIG. 8(A) can be obtained, while for the input evaluation term of "sporty" a display shown in FIG. 8(B) can be obtained.
Finally, at the step S15, upon inspecting the displayed configuration, the operator may change the items and the categories for each design element involved according to his own assessment, and the steps S13 and S14 are repeated in order to have the modified configuration including such changes are re-displayed on the display unit 105. Here, after the inspection, the operator may make the display unit 105 to display another configuration which is inferred by the processing unit 107 to be a less preferable candidate.
Now, such a conventional system for designing automobile interior has the following drawback.
Namely, in the design system described above, a number of categories assigned to each item of the design element is limited to a prescribed number. For example, the patterns for the steering wheel has been limited to only three categories shown in FIGS. 9(A), 9(B), and 9(C) corresponding to three different steering wheel radii of r.sub.1, r.sub.2, and r.sub.3, and the patterns for the instrument panel has been limited to only two categories shown in FIGS. 10(A) and 10(B) corresponding to two different instrument panel thickness of l.sub.1 and l.sub.2.
Consequently, the configuration can be designed only as a combination of a prescribed number of predetermined patterns, even when a subtle variation of certain design element could affect the impression of the entire configuration significantly.